Multivariate standardization techniques using UV-Vis data

Three standardization techniques, namely piecewise direct standardization (PDS), single wavelength standardization (SWS) and centering correction (CC) were applied to multivariate models developed using UV-Vis spectra. The data were obtained for the determination of Ca(II) and Mg(II) in natural waters analysed by sequential injection analysis (SIA). Unlike NIR, changes in measuring conditions are mainly reflected by changes in the sensitivity in the spectra. In all the models tested, the prediction errors in the best standardization conditions were less than one half of those in the non-corrected second conditions. Moreover, bias was not detected by the joint interval test. Of all the standardization techniques assayed, PDS gives the lowest mean squared error of prediction, probably due to the inclusion of more variability in the mapping of the spectra. The influential parameters, such as the number of standardization samples or the window size in PDS, were studied. The larger the number of samples in the standardization subsets, the more effective the techniques are, whereas the variation in window size does not greatly affect the calculations.